Optimizing Electric Vehicle Charging Station Deployment: A Predictive Modeling and Optimization Approach

Owing to extensive environmental advantages, energy optimized processes, and amazing technological innovations, Electric Vehicles (EVs) have become an important domain for research and development. EVs utilize stored electricity power from rechargeable batteries rather than conventional ICE vehicles, which run on gasoline or diesel fuel to power their engines. increasing adoption of electric vehicles (EVs) has placed a strain on the current infrastructure for charging, leading to the need for efficient deployment of EV charging stations. Work done is an effort to identify the areas with the greatest potential for installing EV charging points and suggest the fastest and most affordable charging options. It evaluates current $E V$ adoption trends and utilizes curve-fitting to predict future demand suited for EV charging facilities. It then leverages the Gurobi optimization solver to address cost minimization by allocating demand to charging stations strategically. The results demonstrate the effectiveness of this approach in optimizing EV charging station deployment, achieving an accuracy of over $93 \%$. Notably, Scenario 1 achieved an optimal solution with a cost of INR 3,978,066/-, highlighting the potential cost savings this method offers. Optimizing the deployment of EV charging stations is essential to ensure a smooth shift to ecofriendly transportation and satisfy the rising demand for it.